Authors:
Dong Ik Shin
1
;
Sekyeong Joo
2
and
Soo Jin Huh
2
Affiliations:
1
Asan Medical Center, Korea, Republic of
;
2
University of Ulsan College of Medicine, Korea, Republic of
Keyword(s):
Accuracy, Activity, Daily Life, Sensor, Position, Accelerometer.
Related
Ontology
Subjects/Areas/Topics:
Biomedical Engineering
;
Biomedical Equipment
;
Biomedical Instruments and Devices
;
Biomedical Sensors
;
Devices
;
Health Monitoring Devices
;
Human-Computer Interaction
;
Physiological Computing Systems
Abstract:
The monitoring of single elderly is being more important due to rapid transition to aging society. There are
many bio-signals to monitor the emergent state of elderly. In this paper we propose new criteria to classify
daily life activities using accelerometer and pulse oximeter. We categorized activities with the motility of
real action. The upper most criteria are normal and abnormal activity. The lower criteria are ‘small or large
movement’, ‘periodic or random movement’, ‘no movement or shock’. Then we derive some parameters to
get thresholds to classify these activities according to our new criteria. The main parameters are entropy,
energy and autocorrelation. Some experiments were carried out to determine classifying thresholds. Finally
we got results of classified activities such as ‘no movements’, ‘small movements’, ‘large movements’,
‘periodic movements’ and ‘falls’. We got nearly 100% of classifying result for falls and no movements. In
this case of ‘quasi-emergency
state’ our developing device investigates further status of elderly by
measuring of heart rate and oxygen saturation (SpO2) using pulse oximeter. Finally the device decides in
emergency, it sends a short message to server and then connects to the u-Healthcare centre or emergency
centre and one’s family.
(More)